"We in the basketball stats community need to do a better job communicating. We need to come up with convincing arguments for why we are relevant, why we are not a threat to basketball people, and how we can help basketball people be better at what they do. It will take time, but eventually I think we can do this."

To be able to effectively state this case to NBA teams, we must first be able to state it to ourselves, and, well, I wasn't sure I could. Here's an effort to explain why I'm an APBRmetrician (despite the fact that the name is so lame).

Because everyone uses statistics
As Rosenbaum writes, "Even the oldest of the 'old school' basketball people look at box scores and per game statistics."

The question isn't really whether to use statistics, as some of those hyping the stats versus scouts "feud" in baseball would have you believe, but how much to use them and which statistics to use. Rosenbaum has found a strong relationship between points, rebounds and assists per game and the salaries paid to free agents. However, this "triple crown" set of stats is insufficient to grasp the complexity of the game.

In fact, I'd argue that non-traditional statistics do a better job of matching what scouts talk about in terms of skills. Bad APBRmetricians are primarily concerned with statistics as an end in and of themselves: What is a player's PER, for example? Good APBRmetricians are looking increasingly more and more at measuring player skills and determining how players fit into their roles and together.

Because of my high-school history teacher
Far and away, this is the most bizarre explanation I can come up with, but it also might be the most important. During my last two years at Mt. Rainier High School (no, it's not actually located on or even near the mountain), Ms. Angersbach was my history teacher. Over that period, she effectively managed to permanently convince me of the importance of providing evidence, more evidence and, when in doubt, still more evidence.

Since then, that mentality has permeated my thinking. When it comes to basketball, the best evidence available is usually statistics. So you think Player A is a good rebounder? Terrific, but do his statistics confirm that? Player B is a heady player? Good for him, but does his turnover rate or Roland Rating reflect that?

Not every qualitative basketball statement can be backed up with statistics, but I still find it important to support my claims, as Ms. Angersbach would have told me.

Because I'm subjective
Even though basketball may be my career, I'm still at heart a fan. Over the last four years, I've watched New York rookie Nate Robinson develop from a top football recruit into one of the keys to the turnaround of my alma mater's basketball program. And I'm supposed to be able to put this aside when considering whether Robinson can play in the NBA?

Robinson's statistics, however, are as blind as Lady Justice to the fact that Robinson is one of my all-time favorite players. In situations like that, where I'm too close to the subject to make an objective evaluation, statistics ground my opinion and help keep me from turning from fan to fanboy.

At the same time, a little subjectivity can be a good thing. Many of my favorite players are the scrappy types who proverbially do the "little things" on the court, and I'm excited that with the advent of plus-minus and adjusted plus-minus data from this site, we can do a better job of giving these players credit.

Because I can only watch so much basketball
In addition to the 60-plus NBA and WNBA games I watch in person a year, I try to catch games on TV whenever possible (or now, for the WNBA, the Internet - I'm watching a webcast of the Minnesota Lynx and the New York Liberty as I write this). However, there's a limit to what I can watch, especially if I'm to have some kind of life outside of basketball.

"The reason I'm a stat guy is because I don't have time to watch hundreds of hours of basketball. It's a way for me to follow the game and the players. So I would find stats interesting regardless of whether they provide anything that can't be gotten by watching the game."

I think one of the positions of statistical analysts least understood by traditionalists is that the statistics tell a story. If I look at the NCAA stats of a draft prospect I've never seen play before, they provide me an insight into how that player plays, his background. As scouts compare skills to those of established players they've seen before, so too can we formally or informally use statistics to make that kind of comparison.

Because some of my best friends are APBRmetricians
Roland Beech, John Hollinger, Dean Oliver, Dan Rosenbaum and too many others to name - even if these guys thought WARP was a speed on Star Trek, they would still be brilliant. There's a term for this group, and that term is "select company."

Because it helps me in my day job
It's worth pointing out that my knowledge of statistics helps give my other writing a slightly different perspective. In my case, making Sonics and Storm players look good is part of the job description, and advanced statistics help do that. For example, saying Danny Fortson averaged 7.5 points and 5.6 rebounds per game last season doesn't tell you much about his impact on the Sonics. But if I write that he led the league in true shooting percentage and ranked fifth in rebounding percentage, that's a lot more impressive as well as unique compared to other coverage of the team.

I don't think using statistics fundamentally makes my analysis that much different than that of someone coming from a more traditional perspective. Coming from the background I do, however, I think that using statistics balances out my observations and gives me a more complete perspective than I could without statistics. That's more than enough reason for me.

Kevin Pelton formerly wrote the "Page 23" column for Hoopsworld.com. He provides original content for both SUPERSONICS.COM and storm.wnba.com, where you can find more of his analysis of both the NBA and the WNBA.